464 lines
18 KiB
Python
464 lines
18 KiB
Python
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"""This module contains the _EstimatorPrettyPrinter class used in
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BaseEstimator.__repr__ for pretty-printing estimators"""
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# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
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# 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018 Python Software Foundation;
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# All Rights Reserved
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# Authors: Fred L. Drake, Jr. <fdrake@acm.org> (built-in CPython pprint module)
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# Nicolas Hug (scikit-learn specific changes)
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# License: PSF License version 2 (see below)
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# PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
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# --------------------------------------------
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# 1. This LICENSE AGREEMENT is between the Python Software Foundation ("PSF"),
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# and the Individual or Organization ("Licensee") accessing and otherwise
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# using this software ("Python") in source or binary form and its associated
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# documentation.
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# 2. Subject to the terms and conditions of this License Agreement, PSF hereby
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# grants Licensee a nonexclusive, royalty-free, world-wide license to
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# reproduce, analyze, test, perform and/or display publicly, prepare
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# derivative works, distribute, and otherwise use Python alone or in any
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# derivative version, provided, however, that PSF's License Agreement and
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# PSF's notice of copyright, i.e., "Copyright (c) 2001, 2002, 2003, 2004,
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# 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016,
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# 2017, 2018 Python Software Foundation; All Rights Reserved" are retained in
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# Python alone or in any derivative version prepared by Licensee.
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# 3. In the event Licensee prepares a derivative work that is based on or
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# incorporates Python or any part thereof, and wants to make the derivative
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# work available to others as provided herein, then Licensee hereby agrees to
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# include in any such work a brief summary of the changes made to Python.
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# 4. PSF is making Python available to Licensee on an "AS IS" basis. PSF MAKES
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# NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. BY WAY OF EXAMPLE, BUT
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# NOT LIMITATION, PSF MAKES NO AND DISCLAIMS ANY REPRESENTATION OR WARRANTY OF
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# MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF
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# PYTHON WILL NOT INFRINGE ANY THIRD PARTY RIGHTS.
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# 5. PSF SHALL NOT BE LIABLE TO LICENSEE OR ANY OTHER USERS OF PYTHON FOR ANY
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# INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS A RESULT OF
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# MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON, OR ANY DERIVATIVE
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# THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
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# 6. This License Agreement will automatically terminate upon a material
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# breach of its terms and conditions.
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# 7. Nothing in this License Agreement shall be deemed to create any
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# relationship of agency, partnership, or joint venture between PSF and
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# Licensee. This License Agreement does not grant permission to use PSF
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# trademarks or trade name in a trademark sense to endorse or promote products
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# or services of Licensee, or any third party.
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# 8. By copying, installing or otherwise using Python, Licensee agrees to be
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# bound by the terms and conditions of this License Agreement.
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# Brief summary of changes to original code:
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# - "compact" parameter is supported for dicts, not just lists or tuples
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# - estimators have a custom handler, they're not just treated as objects
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# - long sequences (lists, tuples, dict items) with more than N elements are
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# shortened using ellipsis (', ...') at the end.
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import inspect
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import pprint
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from collections import OrderedDict
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from .._config import get_config
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from ..base import BaseEstimator
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from ._missing import is_scalar_nan
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class KeyValTuple(tuple):
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"""Dummy class for correctly rendering key-value tuples from dicts."""
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def __repr__(self):
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# needed for _dispatch[tuple.__repr__] not to be overridden
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return super().__repr__()
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class KeyValTupleParam(KeyValTuple):
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"""Dummy class for correctly rendering key-value tuples from parameters."""
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pass
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def _changed_params(estimator):
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"""Return dict (param_name: value) of parameters that were given to
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estimator with non-default values."""
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params = estimator.get_params(deep=False)
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init_func = getattr(estimator.__init__, "deprecated_original", estimator.__init__)
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init_params = inspect.signature(init_func).parameters
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init_params = {name: param.default for name, param in init_params.items()}
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def has_changed(k, v):
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if k not in init_params: # happens if k is part of a **kwargs
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return True
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if init_params[k] == inspect._empty: # k has no default value
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return True
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# try to avoid calling repr on nested estimators
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if isinstance(v, BaseEstimator) and v.__class__ != init_params[k].__class__:
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return True
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# Use repr as a last resort. It may be expensive.
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if repr(v) != repr(init_params[k]) and not (
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is_scalar_nan(init_params[k]) and is_scalar_nan(v)
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):
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return True
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return False
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return {k: v for k, v in params.items() if has_changed(k, v)}
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class _EstimatorPrettyPrinter(pprint.PrettyPrinter):
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"""Pretty Printer class for estimator objects.
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This extends the pprint.PrettyPrinter class, because:
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- we need estimators to be printed with their parameters, e.g.
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Estimator(param1=value1, ...) which is not supported by default.
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- the 'compact' parameter of PrettyPrinter is ignored for dicts, which
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may lead to very long representations that we want to avoid.
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Quick overview of pprint.PrettyPrinter (see also
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https://stackoverflow.com/questions/49565047/pprint-with-hex-numbers):
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- the entry point is the _format() method which calls format() (overridden
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here)
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- format() directly calls _safe_repr() for a first try at rendering the
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object
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- _safe_repr formats the whole object recursively, only calling itself,
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not caring about line length or anything
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- back to _format(), if the output string is too long, _format() then calls
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the appropriate _pprint_TYPE() method (e.g. _pprint_list()) depending on
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the type of the object. This where the line length and the compact
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parameters are taken into account.
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- those _pprint_TYPE() methods will internally use the format() method for
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rendering the nested objects of an object (e.g. the elements of a list)
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In the end, everything has to be implemented twice: in _safe_repr and in
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the custom _pprint_TYPE methods. Unfortunately PrettyPrinter is really not
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straightforward to extend (especially when we want a compact output), so
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the code is a bit convoluted.
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This class overrides:
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- format() to support the changed_only parameter
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- _safe_repr to support printing of estimators (for when they fit on a
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single line)
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- _format_dict_items so that dict are correctly 'compacted'
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- _format_items so that ellipsis is used on long lists and tuples
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When estimators cannot be printed on a single line, the builtin _format()
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will call _pprint_estimator() because it was registered to do so (see
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_dispatch[BaseEstimator.__repr__] = _pprint_estimator).
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both _format_dict_items() and _pprint_estimator() use the
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_format_params_or_dict_items() method that will format parameters and
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key-value pairs respecting the compact parameter. This method needs another
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subroutine _pprint_key_val_tuple() used when a parameter or a key-value
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pair is too long to fit on a single line. This subroutine is called in
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_format() and is registered as well in the _dispatch dict (just like
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_pprint_estimator). We had to create the two classes KeyValTuple and
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KeyValTupleParam for this.
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"""
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def __init__(
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self,
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indent=1,
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width=80,
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depth=None,
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stream=None,
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*,
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compact=False,
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indent_at_name=True,
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n_max_elements_to_show=None,
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):
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super().__init__(indent, width, depth, stream, compact=compact)
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self._indent_at_name = indent_at_name
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if self._indent_at_name:
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self._indent_per_level = 1 # ignore indent param
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self._changed_only = get_config()["print_changed_only"]
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# Max number of elements in a list, dict, tuple until we start using
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# ellipsis. This also affects the number of arguments of an estimators
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# (they are treated as dicts)
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self.n_max_elements_to_show = n_max_elements_to_show
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def format(self, object, context, maxlevels, level):
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return _safe_repr(
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object, context, maxlevels, level, changed_only=self._changed_only
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)
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def _pprint_estimator(self, object, stream, indent, allowance, context, level):
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stream.write(object.__class__.__name__ + "(")
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if self._indent_at_name:
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indent += len(object.__class__.__name__)
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if self._changed_only:
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params = _changed_params(object)
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else:
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params = object.get_params(deep=False)
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params = OrderedDict((name, val) for (name, val) in sorted(params.items()))
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self._format_params(
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params.items(), stream, indent, allowance + 1, context, level
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)
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stream.write(")")
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def _format_dict_items(self, items, stream, indent, allowance, context, level):
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return self._format_params_or_dict_items(
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items, stream, indent, allowance, context, level, is_dict=True
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)
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def _format_params(self, items, stream, indent, allowance, context, level):
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return self._format_params_or_dict_items(
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items, stream, indent, allowance, context, level, is_dict=False
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)
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def _format_params_or_dict_items(
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self, object, stream, indent, allowance, context, level, is_dict
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):
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"""Format dict items or parameters respecting the compact=True
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parameter. For some reason, the builtin rendering of dict items doesn't
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respect compact=True and will use one line per key-value if all cannot
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fit in a single line.
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Dict items will be rendered as <'key': value> while params will be
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rendered as <key=value>. The implementation is mostly copy/pasting from
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the builtin _format_items().
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This also adds ellipsis if the number of items is greater than
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self.n_max_elements_to_show.
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"""
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write = stream.write
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indent += self._indent_per_level
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delimnl = ",\n" + " " * indent
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delim = ""
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width = max_width = self._width - indent + 1
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it = iter(object)
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try:
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next_ent = next(it)
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except StopIteration:
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return
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last = False
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n_items = 0
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while not last:
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if n_items == self.n_max_elements_to_show:
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write(", ...")
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break
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n_items += 1
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ent = next_ent
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try:
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next_ent = next(it)
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except StopIteration:
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last = True
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max_width -= allowance
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width -= allowance
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if self._compact:
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k, v = ent
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krepr = self._repr(k, context, level)
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vrepr = self._repr(v, context, level)
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if not is_dict:
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krepr = krepr.strip("'")
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middle = ": " if is_dict else "="
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rep = krepr + middle + vrepr
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w = len(rep) + 2
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if width < w:
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width = max_width
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if delim:
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delim = delimnl
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if width >= w:
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width -= w
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write(delim)
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delim = ", "
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write(rep)
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continue
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write(delim)
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delim = delimnl
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class_ = KeyValTuple if is_dict else KeyValTupleParam
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self._format(
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class_(ent), stream, indent, allowance if last else 1, context, level
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)
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def _format_items(self, items, stream, indent, allowance, context, level):
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"""Format the items of an iterable (list, tuple...). Same as the
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built-in _format_items, with support for ellipsis if the number of
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elements is greater than self.n_max_elements_to_show.
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"""
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write = stream.write
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indent += self._indent_per_level
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if self._indent_per_level > 1:
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write((self._indent_per_level - 1) * " ")
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delimnl = ",\n" + " " * indent
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delim = ""
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width = max_width = self._width - indent + 1
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it = iter(items)
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try:
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next_ent = next(it)
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except StopIteration:
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return
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last = False
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n_items = 0
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while not last:
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if n_items == self.n_max_elements_to_show:
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write(", ...")
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break
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n_items += 1
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ent = next_ent
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try:
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next_ent = next(it)
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except StopIteration:
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last = True
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max_width -= allowance
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width -= allowance
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if self._compact:
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rep = self._repr(ent, context, level)
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w = len(rep) + 2
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if width < w:
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width = max_width
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if delim:
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delim = delimnl
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if width >= w:
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width -= w
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write(delim)
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delim = ", "
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write(rep)
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continue
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write(delim)
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delim = delimnl
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self._format(ent, stream, indent, allowance if last else 1, context, level)
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def _pprint_key_val_tuple(self, object, stream, indent, allowance, context, level):
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"""Pretty printing for key-value tuples from dict or parameters."""
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k, v = object
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rep = self._repr(k, context, level)
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if isinstance(object, KeyValTupleParam):
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rep = rep.strip("'")
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middle = "="
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else:
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middle = ": "
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stream.write(rep)
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stream.write(middle)
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self._format(
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v, stream, indent + len(rep) + len(middle), allowance, context, level
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)
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# Note: need to copy _dispatch to prevent instances of the builtin
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# PrettyPrinter class to call methods of _EstimatorPrettyPrinter (see issue
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# 12906)
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# mypy error: "Type[PrettyPrinter]" has no attribute "_dispatch"
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_dispatch = pprint.PrettyPrinter._dispatch.copy() # type: ignore
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_dispatch[BaseEstimator.__repr__] = _pprint_estimator
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_dispatch[KeyValTuple.__repr__] = _pprint_key_val_tuple
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def _safe_repr(object, context, maxlevels, level, changed_only=False):
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"""Same as the builtin _safe_repr, with added support for Estimator
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objects."""
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typ = type(object)
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if typ in pprint._builtin_scalars:
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return repr(object), True, False
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r = getattr(typ, "__repr__", None)
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if issubclass(typ, dict) and r is dict.__repr__:
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if not object:
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return "{}", True, False
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objid = id(object)
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if maxlevels and level >= maxlevels:
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return "{...}", False, objid in context
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if objid in context:
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return pprint._recursion(object), False, True
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context[objid] = 1
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readable = True
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recursive = False
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components = []
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append = components.append
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level += 1
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saferepr = _safe_repr
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items = sorted(object.items(), key=pprint._safe_tuple)
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for k, v in items:
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krepr, kreadable, krecur = saferepr(
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k, context, maxlevels, level, changed_only=changed_only
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)
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vrepr, vreadable, vrecur = saferepr(
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v, context, maxlevels, level, changed_only=changed_only
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)
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append("%s: %s" % (krepr, vrepr))
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readable = readable and kreadable and vreadable
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if krecur or vrecur:
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recursive = True
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del context[objid]
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return "{%s}" % ", ".join(components), readable, recursive
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if (issubclass(typ, list) and r is list.__repr__) or (
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issubclass(typ, tuple) and r is tuple.__repr__
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):
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if issubclass(typ, list):
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if not object:
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return "[]", True, False
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format = "[%s]"
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elif len(object) == 1:
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format = "(%s,)"
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else:
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if not object:
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return "()", True, False
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format = "(%s)"
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objid = id(object)
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if maxlevels and level >= maxlevels:
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return format % "...", False, objid in context
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if objid in context:
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return pprint._recursion(object), False, True
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context[objid] = 1
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|
readable = True
|
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|
|
recursive = False
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|
components = []
|
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|
append = components.append
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|
level += 1
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|
|
for o in object:
|
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|
|
orepr, oreadable, orecur = _safe_repr(
|
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|
o, context, maxlevels, level, changed_only=changed_only
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|
)
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|
|
append(orepr)
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|
if not oreadable:
|
||
|
|
readable = False
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|
|
if orecur:
|
||
|
|
recursive = True
|
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|
|
del context[objid]
|
||
|
|
return format % ", ".join(components), readable, recursive
|
||
|
|
|
||
|
|
if issubclass(typ, BaseEstimator):
|
||
|
|
objid = id(object)
|
||
|
|
if maxlevels and level >= maxlevels:
|
||
|
|
return "{...}", False, objid in context
|
||
|
|
if objid in context:
|
||
|
|
return pprint._recursion(object), False, True
|
||
|
|
context[objid] = 1
|
||
|
|
readable = True
|
||
|
|
recursive = False
|
||
|
|
if changed_only:
|
||
|
|
params = _changed_params(object)
|
||
|
|
else:
|
||
|
|
params = object.get_params(deep=False)
|
||
|
|
components = []
|
||
|
|
append = components.append
|
||
|
|
level += 1
|
||
|
|
saferepr = _safe_repr
|
||
|
|
items = sorted(params.items(), key=pprint._safe_tuple)
|
||
|
|
for k, v in items:
|
||
|
|
krepr, kreadable, krecur = saferepr(
|
||
|
|
k, context, maxlevels, level, changed_only=changed_only
|
||
|
|
)
|
||
|
|
vrepr, vreadable, vrecur = saferepr(
|
||
|
|
v, context, maxlevels, level, changed_only=changed_only
|
||
|
|
)
|
||
|
|
append("%s=%s" % (krepr.strip("'"), vrepr))
|
||
|
|
readable = readable and kreadable and vreadable
|
||
|
|
if krecur or vrecur:
|
||
|
|
recursive = True
|
||
|
|
del context[objid]
|
||
|
|
return ("%s(%s)" % (typ.__name__, ", ".join(components)), readable, recursive)
|
||
|
|
|
||
|
|
rep = repr(object)
|
||
|
|
return rep, (rep and not rep.startswith("<")), False
|